--- a
+++ b/Scripts/GetResultsVarSelect.R
@@ -0,0 +1,104 @@
+##########################################
+###### AUTOMATIZE READING RESULTS ########
+##########################################
+
+## INPUT : 
+#         1) studyType : name of the IMPACT directory where the results/data are saved
+#         2) method : Method implemented to be analysed (LASSO,RF,GBM,CF)
+#         3) LT : is the data left truncated : TRUE v FALSE
+
+## OUTPUT :
+#         For each of the methods to be analyzed will give 
+#         1) CI distribution bar plot
+#         2) An influence plot of top hit genes
+#         3) Kaplan meier plot based on 4 risk groups
+#         4) Proportion of mutated genes in each of the 4 risk groups, per top hit gene
+
+getResults <- function(studyType,method,geneList){
+
+  
+  load("./Study/Lung/results/Lung_LASSO.Rdata")
+  data <- read.csv("./Study/Lung/data/LungReadyStudy.csv",header = TRUE, row.names = 1)
+  
+  ## determine if left truncated
+  LT = T
+  MD = 12
+  time.type = "Months"
+  
+  ### LASSO ANALYSIS ###
+  
+  #try(setwd("./results/"))
+  
+  if("LASSO" %in% method) {
+    
+    Variables <- colnames(data)
+    allCoefs <- as.data.frame(matrix(nrow=length(LASSO),ncol=length(Variables)))
+    colnames(allCoefs) <- Variables
+    
+    for(x in 1:length(LASSO)){
+      coefsValues <- LASSO[[x]]$fit[,1]
+      allCoefs[x,match(names(coefsValues),colnames(allCoefs))] <- as.numeric(coefsValues)
+    }
+    allCoefs[is.na(allCoefs)] <- 0
+    
+    meanCoefs <- apply(allCoefs,2,function(x){mean(x,na.rm = TRUE)})
+    selectFreq <- apply(allCoefs,2,function(x){
+      length(which(x!=0))/length(x)
+    })
+    
+    ## get mu freq
+    data.temp <- data
+    MutationFrequency <- apply(data.temp,2,function(x){
+      sum(x)/length(x)
+    })
+    
+    resultsAll <- as.data.frame(cbind(meanCoefs,selectFreq,MutationFrequency))
+    colnames(resultsAll) <- c("MeanCoefficient","SelectionFrequency","MutationFrequency")
+    rownames(resultsAll) <- names(meanCoefs)
+    resultsAll <- resultsAll[complete.cases(resultsAll),]
+    resultsAll$GeneName <- rownames(resultsAll)
+    resultsAll$MutationFrequency2 <- cut(resultsAll$MutationFrequency, c(0,0.10,0.20,0.40))
+    
+    if(length(geneList)!=0){
+      m <- resultsAll[match(geneList,rownames(resultsAll)), ]
+      
+      a <- list(
+        x = m$MeanCoefficient,
+        y = m$SelectionFrequency,
+        text = rownames(m),
+        xref = "x",
+        yref = "y",
+        showarrow = TRUE,
+        arrowhead = 7,
+        ax = 20,
+        ay = -40
+      )
+      
+      selectInflPlot <- plot_ly(data = resultsAll, x = ~MeanCoefficient, y = ~SelectionFrequency,
+                                text = ~paste('Gene :',GeneName,
+                                              '</br> Hazard Ratio :',round(exp(MeanCoefficient),digits=2)),
+                                mode = "markers",size = ~MutationFrequency,color = ~MutationFrequency) %>% 
+        layout(title ="Volcano Plot",annotations = a)
+    }
+    
+    else{
+      selectInflPlot <- plot_ly(data = resultsAll, x = ~MeanCoefficient, y = ~SelectionFrequency,
+                                text = ~paste('Gene :',GeneName,
+                                              '</br> Hazard Ratio :',round(exp(MeanCoefficient),digits=2)),
+                                mode = "markers",size = ~MutationFrequency,color = ~MutationFrequency) %>% 
+        layout(title ="Volcano Plot")
+    }
+    
+  }
+  
+  # return(list("ciSummary" = CI.BP,"inflPlot" = influencePlot,"topHits" = topHits,"average.risk"=average.risk,"data.out"= data,
+  #             "selectInflPlot" = selectInflPlot,"MethodUsed" = method,"RiskRefit"=refit.risk,"ClinRefitTable"=ClinRefitTable,
+  #             "RiskHistogram"=RiskHistogram,"LassoFits"=allCoefs,"ClinRefit"=refit.risk.clin,"time.type"=time.type,"MD"=MD,
+  #             "RiskScoreSummary"=as.data.frame(t(summary.RiskScore))))
+ return(list("selectInflPlot" = selectInflPlot))
+}
+#test <- getResults(studyType="Lung",method="LASSO",CNV=FALSE,OnlyCNV= FALSE)
+
+
+# FirstRun <- getResults(studyType="Lung",method="LASSO",CNV=FALSE,OnlyCNV= FALSE,geneList = NULL)
+# save(FirstRun,file="FirstRun.Rdata")